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Kernel machines for non-vectorial data

Abstract:

This work presents a short introduction to the main ideas behind the design of specific kernel functions when used by machine learning algorithms, for example support vector machines, in the case that involved patterns are described by non-vectorial information. In particular the interval data case will be analysed as an illustrating example: explicit kernels based on the centre-radius diagram will be formulated for closed bounded intervals in the real line. © Springer-Verlag Berlin Heidelberg 2007.